(Award available for year: Master of Science)
Subject Specific Learning Outcomes:
Analyse and evaluate issues of power, justice, bias, and the societal impact of AI.
Devise and critically evaluate solutions for major AI-related challenges within professional settings;
Communicate effectively with and tailor complex AI-related information, policy or process for a range of audiences (with appropriate support);
Advocate for responsible use of the technology within and across sectors based on the ability to distinguish appropriate from inappropriate uses of AI;
Apply industry-aligned standards and appropriate regulatory frameworks where appropriate;
Skills Learning Outcomes:
1. The ability to translate and communicate complex technical, ethical and analytical concepts concerning AI, for diverse audiences;
2. The ability to identify, assess and evaluate complex ethical and societal dilemmas in AI implementation;
3. The ability to make well-justified recommendations for appropriate AI use, based on ethical and critical reasoning and evidence, thereby influencing policy and organisational decision-making processes;
4. The ability to conduct an independent research project, tackling a challenge related to AI ethics and society.
Competence Standards:
CS1 Critically evaluate AI systems/use-cases using justified ethical frameworks and credible evidence.
CS2 Design and evaluate context-appropriate responses to AI-related challenges, justifying choices and acknowledging constraints.
CS3 Explain how relevant regulatory, standards, and governance frameworks apply to AI scenarios, including how compliance and accountability would be evidenced in practice.
CS4 Make and justify context-sensitive judgements about when AI use is appropriate, inappropriate, or requires conditions, grounded in risk/benefit reasoning and ethical justification.
CS5 Develop evidence-based, ethically and legally informed recommendations to influence responsible AI practice.
CS6 Communicate complex AI-related information and decisions effectively for different audiences and purposes using mode-neutral choices of format and convention.
CS7 Integrate and critically evaluate perspectives from more than one discipline or sector to investigate real-world AI issues.
CS8 Apply systems thinking to identify interdependencies and likely consequences across technical, social, organisational, and societal dimensions, and use this analysis to inform decisions.
CS9 Plan, manage, and complete a student-led research or practice-based project, demonstrating research integrity and iterative project improvement based on reflection on evidence and process.
CS10 Contribute effectively to interdisciplinary teamwork through coordination, communication, and shared problem-solving using task-appropriate, mode-flexible collaboration approaches.
Approach to assessment:
The assessment design for MSc AI Ethics and Society is intentionally diverse and has been shaped through LISF’s sandpit development model. Assessments were co-produced through structured workshops involving academic colleagues from across faculties, industry partners, professional services, and students. This process ensured that assessment types reflect both academic rigour and real-world relevance, aligning with the programme’s challenge-based and interdisciplinary ethos.
Across the programme, we have adopted a varied portfolio of assessment formats — including essays, policy briefings, podcasts, debates, group projects, and AI-assisted task — in order to develop students’ ability to communicate complex ideas across written, verbal, collaborative and policy-oriented contexts. This diversity reflects the varied environments in which graduates are likely to operate (policy, business, public sector, NGOs, creative industries) and encourages students to develop both individual critical depth and collaborative capacity. Where appropriate, assessments explicitly allow for the responsible use of generative AI tools, reflecting the programme’s commitment to equipping students to engage critically and ethically with emerging technologies in practice.
The LISF Project LABS assessments are designed to scaffold students towards autonomous, interdisciplinary project work. The staged structure — including group discussion, literature review, and substantial independent project — provides progressive development of research, collaboration and critical inquiry skills, enabling students to design and deliver a substantial piece of applied or research-led work addressing a major societal challenge.
Errors, omissions, failed links etc should be notified to the Catalogue Team